Analysis of future power grid loading considering uncertainties for application of risk based grid planning

考虑应用基于风险的电网规划的不确定性的未来电网负荷分析

• 批准号: 394516645
• 负责人: Professor Dr.-Ing. Christian Rehtanz
• 金额: --
• 依托单位: Institut für Energiesysteme, Energieeffizienz und Energiewirtschaft
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/394516645?language=en
• 关键词: Analysis; future; power; grid; loading

The integration of renewable energy plants, the simultaneous dismantling of conventional power plants, the new loads because of sector coupling and the liberalization of energy markets lead to great uncertainties in the future generation of electrical energy and thus also in the load of energy grids. Due to long planning horizons for power lines and cables, investments for grid expansion must be made under existing uncertain future developments.Within the scope of the project, the institute of energy systems, energy efficiency and energy economics from Prof. Christian Rehtanz (ie³) and the research group energy systems (GISE) at the University of Asuncion from Prof. Gerardo Blanco will jointly develop a mathematical and technical overall model that can be used to plan the transmission grid under uncertainties. This enables the determination of future grid loads, taking into account real uncertainties, and the deduction of optimal investment decisions from these. Therefore, the uncertainties must be analyzed and modeled stochastically in a first step. The uncertainties resulting from the localization of the power generation (uncertainties of stage one) are represented using the scenario technique for different time steps. The uncertainties of the second stage, which result after the determination of the localization of the power generation, e.g. through weather uncertainties, are represented by multivariate distribution functions. For this purpose, the copula is used, a function which can determine the relationship between the marginal probability distribution of individual variables. Subsequently, an overall model is derived, which assigns multivariate distribution functions to each scenario of the first stage, so that the input variables for each grid node are modeled by probability density functions (PDF) and their correlations. The results are the input values for the probabilistic load flow calculations which determine the PDF of the line load. For this purpose, the approaches of the point-estimate method are developed further to enable the usage of the method for real grids. The developed method will be verified by Monte-Carlo-simulations. In order to plan the energy grid, a method is then required which makes optimal investment decisions under uncertainties based on the expected line loads. For this purpose, the results of the grid analysis are evaluated first and are concentrated afterwards. Subsequently, a cost function is deducted, which is used as the basis for the application of real option analysis. The approach of path integrals is used for this purpose.This procedure represents a completely new approach compared to the state of the art, where the uncertainties are hardly taken into account and the methods of probabilistic load flow calculations work only on small test grids. Also the coupling of the probabilistic load flow calculations with real option analysis has not taken place, yet, and offers a lot of new possibilities.

可再生能源发电厂的整合、传统发电厂的同时拆除、由于部门耦合而产生的新负荷以及能源市场的自由化，导致未来发电以及能源网负荷的巨大不确定性。由于电力线路和电缆的规划时间较长，电网扩建的投资必须在现有的不确定未来发展的情况下进行。在项目范围内，能源系统研究所，能源效率和能源经济学，来自克里斯蒂安·克兰坦茨教授（ie³）和能源系统研究小组（GISE）Gerardo布兰科教授的Asuncion大学的研究人员将共同开发一个数学和技术的整体模型，可用于规划不确定性下的输电网。这使得能够确定未来的电网负荷，考虑到真实的不确定性，并从中推导出最佳投资决策。因此，必须在第一步中随机地分析和建模不确定性。发电的本地化（第一阶段的不确定性）所产生的不确定性表示使用的场景技术，为不同的时间步长。第二阶段的不确定性（例如，通过天气不确定性）由多变量分布函数表示，所述不确定性在确定发电的定位之后产生。为此目的，使用Copula，一个可以确定单个变量的边际概率分布之间关系的函数。随后，推导出一个整体模型，该模型将多变量分布函数分配给第一阶段的每个场景，从而通过概率密度函数（PDF）及其相关性对每个网格节点的输入变量进行建模。计算结果是概率潮流计算的输入值，用于确定线路负荷的PDF。为此，进一步发展了点估计法的方法，以使该方法能够用于真实的网格。所开发的方法将通过蒙特-卡罗模拟进行验证。为了规划能源网，然后需要一种方法，该方法基于预期的线路负荷在不确定性下做出最优投资决策。为此目的，首先评估网格分析的结果，然后集中。随后，推导出一个成本函数，作为应用真实的期权分析的基础。路径积分法是一种全新的潮流计算方法，与现有的潮流计算方法相比，路径积分法几乎不考虑不确定性，概率潮流计算方法只适用于小的试验网格。此外，概率潮流计算与真实的期权分析的耦合还没有发生，并提供了许多新的可能性。

项目成果

Integrating Real Options Analysis with long-term electricity market models

将实物期权分析与长期电力市场模型相结合

• DOI: 10.1016/j.eneco.2018.12.023
• 发表时间: 2019
• 期刊: Energy Economics
• 影响因子: 12.8
• 作者: Festner;Blanco;Olsina
• 通讯作者: Olsina

Development of an open framework for a qualitative and quantitative comparison of power system and electricity grid models for Europe

开发一个开放框架，用于欧洲电力系统和电网模型的定性和定量比较

• DOI: 10.1016/j.rser.2021.112055
• 发表时间: 2022
• 期刊: Renewable and Sustainable Energy Reviews
• 影响因子: 15.9
• 作者: Syranidou;Matthes;Winger;Linßen;Rehtanz;Stolten
• 通讯作者: Stolten

Long-term assessment of power capacity incentives by modeling generation investment dynamics under irreversibility and uncertainty

通过对不可逆和不确定性下的发电投资动态建模来长期评估电力容量激励

• DOI: 10.1016/j.enpol.2019.111185
• 发表时间: 2020
• 期刊: Energy Policy
• 影响因子: 9
• 作者: Festner;Blanco;Olsina
• 通讯作者: Olsina

Experimental verification of smart grid control functions on international grids using a real‐time simulator

使用实时模拟器对国际电网上的智能电网控制功能进行实验验证

• DOI: 10.1049/gtd2.12486
• 发表时间: 2022
• 期刊: IET Generation, Transmission & Distribution
• 作者: Palaniappan;Molodchyk;Shariati-Sarcheshmeh;Schlichtherle;Richter;Appiah Kwofie;Rios Festner;Blanco;Mutule;Borscevskis;Rafaat;Häger;Rehtanz
• 通讯作者: Rehtanz